1. Technical Field
The present disclosure relates generally to determining a direction of arrival of multiple signals incident on a sensor, and more particularly to methods and systems to determine the direction of arrival of multiple signals incident on a tripole sensor.
2. Discussion of Related Art
Electromagnetic signals or radiation are self-propagating waves in a vacuum or in matter. Electromagnetic signals include electric and magnetic field components that oscillate in phase perpendicular to each other and perpendicular to the direction of energy propagation. Electromagnetic signals can be classified into several types according to the frequency of its wave, including radio waves, microwaves, terahertz radiation, infrared radiation, visible light, ultraviolet radiation, X-rays and gamma rays.
In the field of astronomy, electromagnetic signals are studied because they may pass through gas and dust in space, and terrestrial atmospheres with little distortion. Given this property, there is an interest in the scientific community to expand the exploration of the radio signal spectrum, for example, to image and understand various astronomical phenomena. Such exploration may help scientists to understand the transient sky, to probe accretion onto black holes, to identify orphan gamma-ray burst afterglows, to discover new and unknown transient phenomena from currently undiscovered celestial objects, etc.
More generally, sensors (e.g., a radio antenna) may be used to receive the electromagnetic signals for subsequent study. However, it can be difficult to identify the direction of arrival (DOA) of an electromagnetic signal incident on a sensor, especially in the presence of multiple such signals, interference, and noise. When multiple signals are incident on the sensor, the result is a superimposed combination, which can make it difficult to identify the individual signals of interest. DOA estimation is related to Blind Source Separation, which is the separation of a set of signals from a set of mixed signals, with little or no information about the source signals or the mixing process. Conventional approaches for DOA estimation use a spatially distributed array of multiple sensors (e.g., multiple antennas) to disambiguate the multiple signals of interest. With the use of multiple sensors, various techniques are available for DOA estimation. These techniques include phase-based interferometry methods, Eigen decomposition methods, and machine learning methods.
Phase interferometry (PI) based methods use measured phase differences across an array of sensors to estimate the DOA. While a PI based method can be applied to simple radar signals, it is not as useful when the signals become more complex. Decomposition techniques exploit correlations inherent in time-dependent signals to estimate the components and the direction of the incoming signals. These approaches include the Multiple Signal Classification (MU-SIC) algorithm, Maximum Likelihood Methods, and Estimation of signal parameters via rotational invariance techniques (ESPRIT) for narrow-band planar signals. These approaches offer asymptotically unbiased estimates of the direction of the irradiating sources, but are computationally expensive and not easily implemented in a real-time environment. Machine learning techniques may perform well, but their success is contingent on the availability of a sufficiently large training set, especially for large-scale radio astronomy observations.
Recent advances in antenna design have led to the development of a practical tripole antenna that receives all three components (e.g., x, y, and z dimensions) of incident electromagnetic signals in terms of the resulting electric field or generated current. For a single incident wave, the DOA may be directly computed from a measurement of these three components. However, when multiple waves with different frequencies are incident on a single tripole sensor, it can be difficult to compute the DOA.
Thus, there is a need for methods and systems that can determine a direction of arrival of multiple signals incident on a tripole sensor.